10-Biometrics-Lecture-10-Part2-2008-11-24

10-Biometrics-Lecture-10-Part2-2008-11-24 - 1 Biometrics

Info iconThis preview shows pages 1–10. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 1 Biometrics http://scgwww.epfl.ch/courses Master SC Information and Communication Security Dr. Andrzej Drygajlo Speech Processing and Biometrics Group Signal Processing Institute Ecole Polytechnique Fdrale de Lausanne (EPFL) Center for Interdisciplinary Studies in Information Security (ISIS) 2 Speaker Recognition Dynamic Signature Fingerprints Iris Face Hand Others Multimodal Biometrics Leading Biometric Technology 3 Multimodal Biometrics Generalities Challenges in biometric recognition Limitations of unimodal biometric system What to integrate? Integration Strategies Performance evaluation Integration of soft biometric traits Summary 4 Multimodality Facial Features Iris Hand Geometry, Palm Veins and Fingerprints Voice Quack Quack 5 References L. Hong, A. Jain, Multimodal Biometrics , chapter 16 in A. Jain, R. Bolle, S. Pankanti, Biometrics: Personal Identification in Networked Society , Kluwer Academic Publishers, Norwell, 1999. A. Ross, K. Nandakumar, A. Jain, Handbook of Multibiometrics , Springer, New York, 2006 Multimodal Biometric Systems , chapter 7 in D. Maltoni, D. Maio, A.K. Jain, S. Prabhakar, Handbook of Fingerprint Recognition , Springer-Verlag, New York, 2003. Integrating Information , chapter 11 in R.M. Bolle, J.H. Connell, S. Pankanti, N.K. Ratha, A.W. Senior, Guide to Biometrics , Springer-Verlag, New York, 2004 6 Biometric Systems Unibiometric system is a system that uses only a single biometric identifier Unimodal biometric system is a subset of a unibiometric system that uses a single instance (snapshot), a single representation, and a single matcher for a recognition decision Multi-biometric system is a biometric system that uses more than one independent or weakly correlated biometric identifier taken from an individual (e.g., fingerprint and face of the same person, or fingerprints from two different fingers of a person, respectively) Multimodal biometric system is a superset of a multi-biometric system that may use more than one correlated biometric measurement, e.g., multiple impressions of a finger, multiple images of a face in a video, multiple representations of a single input, multiple matchers of a single representation, or any combination thereof. The definition of a unimodal biometric system is the most restrictive and the definition of a multimodal biometric system is the most general . 7 Biometric Characteristics (Modalities) 8 Which Biometric is the Best? Universality (everyone should have this trait) Uniqueness (everyone has a different value) Permanence (should be invariant with time) Collectability (can be measured quantitatively) Performance (achievable recognition accuracy, resources required, operating environment) Acceptability (are people willing to accept it?) Circumvention (how easily can it be spoofed?) 9 Multimodal Biometrics...
View Full Document

Page1 / 48

10-Biometrics-Lecture-10-Part2-2008-11-24 - 1 Biometrics

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online